We present an integrated approach for supporting in-network sensor data processing in dynamic and heterogeneous sensor networks. The concept relies on data stream processing techni...
We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of hu...
In recent work, Kalman Filtered Compressed Sensing (KF-CS) was proposed to causally reconstruct time sequences of sparse signals, from a limited number of “incoherent” measure...
Automated event extraction remains a very difficult challenge requiring information analysts to manually identify key events of interest within massive, dynamic data. Many techniq...
Abstract We discuss data production rates and their impact on the performance of scientific applications using parallel computers. On one hand, too high rates of data production c...
Terry W. Clark, L. Ridgway Scott, Stanislaw Wloked...